posebusters 0.6.5

PoseBusters: Plausibility checks for generated molecule poses.

Paper in Chemical Science and preprint on arXiv

Installation

# install with pip from PyPI
pip install posebusters

Usage

# Check generated molecule pose.
bust molecule_pred.sdf
bust molecule_a.sdf molecule_b.sdf
bust molecule_*.sdf

# Check new ligand generated for a given protein.
bust ligand_pred.sdf -p mol_cond.pdb

# Check re-docked ligand (a pose that should recover the ligand in a given protein-ligand crystal complex).
bust ligand_pred.sdf -l mol_true.sdf -p protein.pdb

# Check any of the three by providing a csv with files to check together
bust -t file_table.csv

Documentation

Documentation is available at https://posebusters.readthedocs.io.

For more information about the tests and for a study using PoseBusters to compare docking methods, refer to our paper or preprint:

@article{buttenschoen2024posebusters,
  title = {{{PoseBusters}}: {{AI-based}} Docking Methods Fail to Generate Physically Valid Poses or Generalise to Novel Sequences},
  shorttitle = {{{PoseBusters}}},
  author = {Buttenschoen, Martin and Morris, Garrett M. and Deane, Charlotte M.},
  year = "2024",
  journal = "Chemical Science",
  volume = "15",
  issue = "9",
  pages = "3130-3139",
  publisher = "The Royal Society of Chemistry",
  doi = "10.1039/D3SC04185A",
  url = "http://dx.doi.org/10.1039/D3SC04185A",
}

The data used for the paper is available at https://zenodo.org/record/8278563.

Feedback & Contact

We welcome all feedback. For code issues, please open an issue. For other inquiries contact us by email.

Thanks

This program uses software written by other people. Notably:

• RDKit - https://github.com/rdkit/rdkit
• Pandas - https://github.com/pandas-dev/pandas